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INSIGHTS Document Transcript

  • 1. TARGET DATE FUND RESEARCH INSIGHTS Sharpening Your Aim Selecting the best target date strategy for your participants
  • 2. About JPMorgan Asset Management — Global Multi-Asset Group The Global Multi-Asset Group (GMAG) has been managing portfolios on behalf of institutional investors, including defined contribution and defined benefit pension plans, endowments and foundations for more than 25 years. The group, which consists of more than 40 investment profes- sionals with an average of 10 years of industry experience, combines its capital markets, strategic and tactical asset allocation, portfolio construction and active risk budgeting capabilities with one of the broadest product offerings in the industry. JPMorgan’s variety of return sources extends across asset classes, geographies and proven investment methodologies. This global product palette provides GMAG’s experienced multi-asset class investment specialists with access to the ideal, low correlation building blocks necessary for structuring efficiently diversified portfolios. SmartRetirement, the group’s target date strategy, provides defined contribution plan sponsors and participants with institutional-quality investment solutions. Our fund design combines the skills and asset classes to which our most sophisticated defined benefit plans have access, with nearly 20 years of insights on participant behavior from JPMorgan Retirement Plan Services, recognized as one of the most innovative and participant-focused recordkeepers in the industry. SmartRetirement Portfolio Management Team Anne Lester Patrik Jakobson Michael Schoenhaut Managing Director Managing Director Vice President Senior Portfolio Manager Senior Portfolio Manager Head of Portfolio Implementation Global Multi-Asset Group Global Multi-Asset Group and Strategy Global Multi-Asset Group Katherine Santiago Daniel Oldroyd Quantitative Research Analyst Vice President Global Multi-Asset Group Portfolio Manager Global Multi-Asset Group
  • 3. Foreword In our recent research paper — Ready! Fire! Aim? — JPMorgan Asset Management addressed the question of whether target date strategies are delivering on their full potential to help 401(k) participants meet retirement funding needs. There were two key findings in that paper: • 401(k) participant behavior is much more varied and volatile than most standard industry models assume. These conclusions were based on a rigorous, quantitative examination of the contribution and withdrawal patterns of 1.3 million 401(k) participants — a proprietary database of participants whose accounts are administered by JPMorgan Retirement Plan Services. • Highly diversified target date strategies that include extended and alternative assets (e.g., emerging equity, emerging debt, direct real estate, REITs, and high yield fixed income) may help a higher percentage of partici- pants reach retirement with the 401(k) balance necessary to provide income security and maintain their lifestyle — an important measure of success for plan sponsors. We received a great deal of positive response to that paper, as well as questions about how to apply this knowl- edge. Many questions centered on the issue of variability among individual companies or industry groups, and whether that variance might impact target date strategy selection for a particular plan. The most efficient way to address these questions was to analyze industry cohorts and then compare them to profiles of individual companies in those industries. Based on these comparisons, we concluded that industry data does provide a useful proxy for individual companies. This paper reports the results of our industry-level analysis. In brief, while we were able to identify industry variations, these findings did not change our original conclusions about the benefits of highly diversified target date strategies, specifically those that include substantive allocations to extended and alternative assets throughout the investment horizon. Our latest analysis demonstrates that these types of products — which can offer comparable returns with lower volatility than more traditional designs — may give participants the greatest downside protection, regardless of industry. In addition, throughout this paper, we emphasize the difficulty of changing participant behavior, which makes target date design an even more critical decision for plan sponsors. Choosing a well-designed target date strategy is one way that sponsors can reliably offset behavioral influences and help participants reach their retirement funding targets — a key measure of plan success. We hope that both of these papers will be useful in choosing the best and most appropriate products for your par- ticipants, and in helping them retire with the income they need. In addition, we owe our clients a great deal of thanks for their continued support as well as their engagement with our portfolio management and research teams. This paper exemplifies the kind of groundbreaking work that results from true partnership. If you have any questions, or would like further information on any of these topics, please contact your JPMorgan Asset Management representative. Sincerely, Anne Lester Katherine Santiago Managing Director Quantitative Research Analyst 212-648-0635 212-648-1879 anne.lester@jpmorgan.com katherine.s.santiago@jpmorgan.com
  • 4. Sharpening Your Aim Table of Contents Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Industry-specific behavior patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 • Salary • Contributions • 401(k) Loans • Withdrawals Interaction of multiple behaviors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Testing target date designs across industries and companies . . . . . . . . . . . . . . . . . . 7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Appendices A. Potential portfolio outcomes based on industry-specific behavior patterns . . . . 14 B. JPMorgan Asset Management long-term capital market return assumptions . . 16 C. Income replacement summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Editor Barbara Heubel Vice President Institutional Investment Marketing barbara.m.heubel@jpmorgan.com
  • 5. Overview For many people, defined contribution (DC) plans factors affecting 401(k) portfolio outcomes — and have supplanted defined benefit (DB) plans as a pri- hence the ultimate “success” of those plans. mary source of retirement income. As a result, plan We propose that a reasonable measure of success — sponsors are under increasing pressure to demonstrate and a definable, prudent objective for plan sponsors DC plan success, which is ultimately determined by — is to help the highest number of retirees achieve an the level of comfort and security achieved by partici- annuity funding level sufficient to maintain their pre- pants at retirement. retirement lifestyles. With 25 years of experience managing multi-asset In trying to achieve this goal, however, sponsors can be portfolios for institutional investors, JPMorgan Asset undermined by participants’ own behavior, which is Management is uniquely positioned to help address this much more volatile and varied than the simplified challenge. Our Global Multi-Asset Group consists of assumptions built into many target date fund simula- more than 40 investment professionals, with an average tions. Our data show that participant behavior diverges of 10 years of industry experience, and a range of capa- significantly from simplified assumptions in five key bilities that spans capital markets, strategic and tactical areas (Exhibit 1), any one of which could have a mate- asset allocation, portfolio construction and active risk rial impact on success rates. Moreover, our experience budgeting. Likewise, JPMorgan Retirement Plan suggests to us that these behavioral variations are likely Services (RPS), with nearly 20 years of DC plan experi- to persist, in spite of plan features (e.g., auto-enroll- ence, is recognized as one of the most innovative and ment, auto-escalation) designed to address some of participant-focused recordkeepers in the industry. them. Taken all together, these issues present not only In our previous paper — Ready! Fire! Aim? — we a serious plan management challenge, but also point to used our proprietary recordkeeping database to flaws in the industry’s current analytical framework. develop groundbreaking research into the behavioral Exhibit 1 — Participant behavior assumptions Simplified assumptions versus… Reality: JPMorgan All Industries findings** Contributions* Rates start at 6%, increase year-by- On average, contribution rates start at 6% and year, reaching 10% of salary by increase slowly, reaching 8% of salary by age 40, age 35 and 10% not until age 55 Salary raises Participants get a raise every year On average, participants get raises every 2 out of 3 years Loans Participants don’t borrow 20% of participants borrow, on average, 15% of account balance; 35% repeated Pre-retirement Premature distributions 15% of participants over the age of 59½ withdraw, distributions don’t happen on average, 25% of assets In retirement Participants withdraw a The average participant withdraws over 20% distributions consistent 4%–5% annually per year at or soon after retirement Sources: AllianceBernstein “Target-Date Retirement Funds — A Blueprint for Effective Portfolio Construction,” October 2005; JPMorgan Retirement Plan Services participant database, 2001–2006 * These numbers do not include employer contributions, which we assume for modeling purposes in our research to be 3%. ** Throughout this research, the JPMorgan All Industries behavior composite is an aggregate measure of behavior characteristics over the entire RPS population from 2001 to 2006, with insignificant variations from aggregate behaviors observed during the period 2003–2006. This total population includes a limited number of companies outside of the ten industries discussed in this research. 1
  • 6. Against this backdrop, we evaluated the performance • Shortening the time period to 2003–2006, to take potential of a current industry favorite: target date advantage of the recent growth of JPMorgan strategies. (See Ready! Fire! Aim? — March 2007.) Retirement Plan Services and maximize the size, We found that broadly diversified strategies — in consistency, and statistical significance of the popu- which extended and alternative assets comprise over lation sample within each industry.1 20% of the portfolio for the entire investment horizon • Analyzing characteristics of participant behavior, to — may help the largest number of participants reach distinguish any clear industry-specific behaviors their annuity targets. This beneficial effect held true from random noise, especially in the areas of cash even after accounting for the interaction of volatile inflows (e.g., contribution rates), outflows (e.g., participant behavior with volatile investment returns. loans and withdrawals), and salary growth. These earlier findings, however, did not address ques- • Performing scenario-testing of the same four target tions of company and industry variance, which were date designs as in our original research (Aggressive, raised by JPMorgan Asset Management clients: Conservative, Concentrated, and broadly diversified • If actual participant behavior varies significantly SmartRetirement) — this time using specific from current models, could there be even more vari- behavior data for ten different industries. ance hiding within specific companies or industries? In the end, we found that there is considerable vari- • Would this variance affect the selection of appropri- ability in behavior across industries. However, unless a Plan success ate target date strategies for those plans? plan’s participant behavior/pattern of cash flows is means helping very different from the average plan, the result (i.e., As recordkeeper to nearly 200 firms offering 401(k) the most the best choice for a target date strategy) is likely to plans to 1.3 million participants, JPMorgan participants be the same. And given the persistence of less-than- Retirement Plan Services provides a robust database ideal participant behavior — which appears to be hav- achieve retirement for answering these questions. We went back to the ing a material effect on success rates — choosing the income security original population sample, used in the previous right target date design may be one of the most paper, but this time we were not interested in average important decisions a plan sponsor can make. Over behavior. The target was industry-specific behavior, the long term, diversification into extended and alter- and the key elements of our approach included: native assets, not merely a higher allocation to equi- • Breaking nearly 200 clients into ten different ties, is still the most effective tool for improving risk- groups (Exhibit 2), as determined by the Global adjusted returns and providing the downside protec- Industry Classification System (GICS) sector and tion needed by most participants. industry definitions. Exhibit 2 — Industry groups within the sample population Number Participant Average plan Name GICS industry group of clients size asset size ($) Consumer Durables Consumer Durables & Apparel/Retail 26 191,023 327,957,397 Consumer Services Media/Consumer Services 13 81,616 321,181,345 Consumer Staples Food Beverage/Household Products 12 114,803 1,271,980,894 Energy Energy 8 34,220 353,780,422 Financials Bank 11 188,988 1,279,207,546 Healthcare Healthcare Equipment and Services 16 107,468 396,210,501 Industrials Capital Goods/Comm Svcs & Supplies 43 126,992 292,960,013 Information Technology Semiconductors & Semi Equipment 19 87,062 381,407,897 Materials Materials 21 119,871 431,886,237 Utilities Utilities 9 37,707 455,166,517 Source: JPMorgan Retirement Plan Services participant database, 2003–2006 1 Behavior observed over this time period was not materially different from that observed using the previously employed 2001–2006 time frame. 2
  • 7. Industry-specific behavior patterns The growing importance of wealth accumulation in designs that can provide optimal downside protection 401(k) plans puts increasing pressure on sponsors to to participants whose behavior makes them vulnerable understand all the factors — behavioral as well as to shortfalls in retirement funding. In the end, we investment — that can affect plan success. found that across all industries target date strategies emphasizing diversification and downside protection To begin, we know that a significant driver of success were most likely to help the greatest number of par- is how the size and timing of portfolio inflows and ticipants achieve retirement funding success. outflows interact with the size and timing of market returns. Portfolio transactions, however, are in a par- The following discussion and illustrations highlight ticipant’s control, not the sponsor’s. Participants’ the wide range of dispersion we found in participant explicit preliminary choices (initial contribution levels behavior across a number of industries. Our cohort and asset allocation) and their continual actions research focused on four critical behavioral areas: sal- (changes in contributions, loans and withdrawals) can ary, contributions, 401(k) loans, and withdrawals. have a material impact on the volatility of portfolio cash flows, and thereby the portfolio itself. Salary Unfortunately, experience has taught us that partici- Salary is one of the most critical drivers of participant pants’ saving and investing behaviors are hard to behavior because it defines the limit on the pool of change without direct intervention. Plan sponsors available assets. In this latest analysis, the data sug- have tried to promote change using plan features, such gests a wide dispersion of salaries across ages and as auto-enrollment and auto-escalation. But our latest industries (Exhibit 3-A). Comparing average salaries real-world observations show persistent and wide vari- across different participant groups and ages can be dif- ations in savings and investment behaviors, which, in ficult, due to varying demographics or generational many cases, are compromising participants’ success. influences. The data, however, does describe a clear and drastic variability of salaries that can occur In light of how difficult it is to change behavior, and between different subgroups of participants. in lieu of comprehensive progress in this area, plan sponsors must do all they can to address behavioral While the salaries of retiring participants can vary influences using other measures. One of the most across industry, the speed and path of participants get- important measures is adopting target date fund ting to those salaries may vary even more. In addition, Exhibit 3: Salary by industry A: Average salary levels* B: Average annual probability of a raise Materials Information Technology Utilities $100,000 Financials 100% All Industries Consumer Services All Industries 90% Financials Consumer Durables $80,000 80% 70% $60,000 60% 50% $40,000 40% $20,000 30% 25 30 35 40 45 50 55 60 65 25 30 35 40 45 50 55 60 65 Age Age Source: JPMorgan Retirement Plan Services participant data base, 2003–2006 We do not show results for all ten industries; we include only the high and low outliers and the median. Industries not shown can be assumed to lie between the highest and lowest results. * The decline in average salary with age is due to the earlier retirement of higher (versus lower) salaried employees. 3
  • 8. a large amount of dispersion was found across ages and Industrials, the average rate was 35%. By comparison, industries with respect to the frequency of raises only 20% of participants in the Consumer Staples indus- (Exhibit 3-B). While the average participant will try change their contribution rates. receive a raise about two out of every three years, or about 67% of the time, the frequency of raises can 401(k) Loans range from only 50% (every other year) up to nearly While, on average, 20% of participants have a loan out- 100% (every year). standing in any given year, and most industries huddle The dispersion around the size of raises (as a percent- around this average during the peak ages for loans, some age of current salary) is just as diverse as their fre- industries’ participants have more unique behavior quency. Many industries see relatively frequent wage (Exhibit 5-A). The Materials industry, for example, growth of close to inflation. Some receive wage takes loans more frequently, reaching 30% of partici- growth below inflation, depending on market condi- pants between the ages of 35 and 50. Participants in tions. Still other industries experience much larger but industries such as Consumer Services and Info Tech are less frequent salary increases. about a third as likely (10%) to take out a loan. On average, the frequency of raises is inversely related There is similar variability in the tendency toward to the size of those raises. That relationship, however, taking multiple loans (Exhibit 5-B). Going back to can change dramatically over the length of a partici- the Info Tech industry, only 20% of participants with There is wide pant’s career. In several industries, such as Financials, loans will have more than one loan outstanding in a annual salary growth starts out at over 15% early in a year. In contrast, in the Financials industry, an average dispersion in participant’s career, but then quickly declines to a of 20% of participants will take a loan, but 60% of participant those participants will have multiple loans outstand- more normal rate. behavior across ing in a year. industries Contributions Withdrawals The next big question is: What do participants in dif- ferent industries do with their pool of available The behavior with the most significant impact on resources? How much do they contribute and how cash-flow volatility is account withdrawals. Again, we often do their contributions change? see a significant level of variability in the frequency and size of withdrawals across industries (Exhibit Despite significant differences in the average contribu- 6-A). Most industries hover around the average: Each tion rates from industry to industry, contributions for year 15% of participants between the ages of 59½ and participants first entering their plans are relatively sim- 65 take withdrawals. Yet industries such as Consumer ilar (Exhibit 4-A). Across all industries, participants Durables have almost twice as many participants, or who contribute begin with an annual contribution rate 25%, making withdrawals, and those withdrawals of about 6% of salary, on average.2 Contribution rates, average 25% of their balance (Exhibit 6-B). however, gradually diverge as retirement approaches. (We note that plan design itself may be a contributing factor The percentage of participants each year on average, in the wide dispersion we see across industries. For example, making changes to their contribution rates varies signifi- if certain plan features were more common in a specific cantly across industries (Exhibit 4-B). For example, on industry — e.g., allowing/disallowing 401(k) loans — average, 30% of all participants in our sample changed then that industry’s preferences in plan design would be a their contribution rates in a given year. However, within strong contributor to its participant behavior profile.) 2 These numbers do not include employer contributions, which we assume for modeling purposes in this research to be 3%. 4
  • 9. Exhibit 4: Contributions by industry B: Average percent of participants changing A: Average contribution rate contribution rate Industrials Utilities 50% 14% All Industries All Industries Healthcare Financials 40% Consumer Staples 12% Consumer Staples 30% 10% 20% 8% 10% 6% 0% 4% 25 30 35 40 45 50 55 60 65 25 30 35 40 45 50 55 60 65 Age Age Source: JPMorgan Retirement Plan Services participant data base, 2003–2006 Exhibit 5: Loans by industry B: Average percent of borrowers with multiple loans A: Average percent of participants taking loans outstanding Financials 50% Materials 80% All Industries All Industries Consumer Durables 40% Info Tech Info Tech Consumer Services 60% 30% 40% 20% 10% 20% 0% 0% 25 30 35 40 45 50 55 60 65 25 30 35 40 45 50 55 60 65 Age Age Source: JPMorgan Retirement Plan Services participant data base, 2003–2006 Exhibit 6: Withdrawals by industry A: Average percent of participants taking withdrawals B: Average withdrawal as percent of total balance 35% Consumer Durables Info Tech 40% Energy Consumer Durables 30% All Industries All Industries Utilities 35% 25% Utilities Energy 20% 30% 15% 25% 10% 5% 20% 0% 15% 40 45 50 55 60 65 70 75 45 50 55 60 65 70 75 Age Age Source: JPMorgan Retirement Plan Services participant data base, 2003–2006 Our intent in all line graphs — Exhibits 3, 4, 5 and 6 — is to show the wide range of results among the industries we studied. Therefore, we do not show results for all ten industries; we only include the high and low outliers and the median. If an industry is not shown on the graph, assume that it would be plotted somewhere between the highest and lowest results. For further details, see Exhibit 13 on page 12 or the supplemental industry summary sheets — available at jpmorgan.com/insight or through your JPMorgan representative, if not provided with this report. 5
  • 10. Interaction of multiple behaviors While individual behaviors may add to portfolio vola- industry begin contributing at an average rate of 6%, tility and impact expected outcomes, the cumulative similar to the overall population average. But a lower- impact of multiple behaviors (on the portfolio and than-average share of these participants make annual each other) can be even more dramatic. changes to their contribution rates. As a result, the average participant in this industry reaches a contribu- For example, consider the effect of loan behavior on tion rate of only 8%, and does so much later than contribution rates. Not only does a loan reduce the average, by age 50. However, while the participants in amount of the portfolio experiencing market move- this industry save less, they also withdraw less prior to ments, it also has a negative impact on contribution retirement. This behavior counters some of the effect rates. The majority of participants taking loans lower of saving less by leaving more of their balance intact their contribution rates, or even stop contributing for retirement. altogether during the repayment period. This com- bined behavior can produce significant negative effects How might those balances be affected if these partici- if the loan coincides with strong market performance. pants were forced to save more? One could speculate that forcing increases in savings could result in higher Another interaction we observed was that low savings withdrawal rates. In other words, even where plan often correlated with low withdrawals and high sav- sponsors achieve a higher savings rate through plan ings with high withdrawals. An example of an indus- design, if it is not accompanied by changes in partici- try with low savings combined with low withdrawals Participant pants’ attitudes and behaviors, sponsors cannot count is Consumer Staples (Exhibit 7). Participants in this behavior is on those hard-won savings actually staying in the plan. difficult to modify and can Exhibit 7 — Cumulative behaviors in the Consumer Staples industry materially impact Simplified assumptions JPMorgan All Industries JPMorgan Consumer Staples industry Contributions Rates start at 6%, increase year-by-year, Contribution rates start at 6% and Contribution rates start near 6% and portfolio results reaching 10% of salary by age 35 increase slowly, reaching 8% of salary increase slowly, reaching 8% of salary by age 40, and 10% not until age 55 by age 50 Salary raises Participants get a raise every year On average, participants get raises On average, participants get raises every 2 out of 3 years every 2 out of 3 years Loans Participants don’t borrow 20% of participants borrow, on average, 20% of participants borrow, on average, 15% of account balance; 35% repeated 15% of account balance Pre-retirement Premature distributions don’t happen 15% of participants over the age of 59½ 15% of participants over the age of 59½ distributions withdraw, on average, 25% of assets withdraw, on average, 20% of assets In retirement Participants withdraw a The average participant withdraws over The average participant withdraws over distributions consistent 4%—5% annually 20% at or soon after retirement 20% at or soon after retirement Sources: AllianceBernstein “Target-Date Retirement Funds — A Blueprint for Effective Portfolio Construction,” October 2005; JPMorgan Retirement Plan Services participant database, 2003–2006 6
  • 11. Testing target date designs across industries and companies We now know that industries can have very different diversifying component of the SmartRetirement design behavior profiles varying across multiple behavior across the investment horizon. dimensions. The open question is: Should any of these In a similar approach to our initial paper, we put our industry-specific behavior patterns impact plan sponsors’ tar- model to work combining each industry’s participant get date strategy selections? cash flow volatility with the volatility and sequence of To get an answer, we compared potential portfolio market returns. The model output was a range of outcomes for participants in ten different industries, expected portfolio outcomes, based on 10,000 simu- under four different target date strategies (Aggressive, lated market environments. Concentrated, Conservative, and broadly diversified Exhibit 8 compares the expected portfolio outcomes for SmartRetirement). The results of our scenario testing Consumer Staples versus the JPMorgan All Industries confirm that behavioral differences across industries total. The red line on each chart marks the income should not materially impact the selection of a target replacement target — the balance at retirement needed date design. To illustrate, we offer two examples of to purchase an annuity to generate the roughly 40% of industry-specific portfolio outcomes (Consumer Sta- pre-retirement income required, in addition to Social ples and Financials) compared to the JPMorgan All Security, to maintain a pre-retirement lifestyle. (See Cross-industry Industries average. By “outcome” we mean the group’s Appendices A and C for notes on reading these charts variations in distribution of 401(k) balances at retirement, relative and calculating income replacement targets.) to its income replacement target. behavior do not Average salary growth in the Consumer Staples imply differences In the sidebar on the following page, we show the allo- industry (Exhibit 7) results in an income replacement cation glide paths for each of the four strategies — in the target date target similar to the JPMorgan All Industries average indicating key differences in their strategic asset alloca- of $400,000. However, despite lower-than-average strategy most tions over a participant’s working life and beyond. It is withdrawals, industry participants’ below-average likely to help notable that the SmartRetirement design holds a wider savings decreases median expected portfolio balances spectrum of assets over the participant’s entire career. It participants by almost $80,000 on average versus the All Indus- holds fewer equities at the outset than the other strate- succeed tries medians. Lower-than-average expected portfolio gies and decreases equity allocation more rapidly than balances mean a lower expected success rate in reach- Aggressive and Concentrated designs. Extended and ing income replacement targets, emphasizing the alternative assets, on the other hand, are a sizeable, need to focus on downside protection. Exhibit 8: Comparing expected portfolio balances at retirement — JPMorgan All Industries versus Consumer Staples Range of expectations with JPMorgan All Industries behavior Range of expectations with Consumer Staples behavior (000s) (000s) 1,500 Percentile 1,500 5% 25% 1,200 50% 1,200 75% 900 95% 900 814 717 747 681 626 636 597 600 551 551 600 512 500 462 466 444 471 385 410 385 $400 362 357 $400 329 350 318 299 300 236 260 300 228 224 199 205 225 201 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Results are based on JPMorgan Asset Management Long-Term Capital Market Return Assumptions, 2006, JPMorgan Asset Management and industry prospectuses. See Exhibit 7 for Consumer Staples participant behavior assumptions. All dollar values are inflation-adjusted. 77
  • 12. Comparing asset allocation glide paths In researching the portfolio composition and simulated investment outcomes of target date funds, we have identified three common categories of fund design that we will refer to as Aggressive, Concentrated and Conservative. Each strategy starts out holding mostly equities and then switches over to large allocations of bonds or cash at the end. But the dynam- ics of the shift, as well as the addition of diversifying extended and alternative assets, vary considerably across the three fund designs and make a significant difference to the overall results. Based on actual funds in the marketplace, the graphs below illustrate the projected portfolio allocations over time for the three types of strategies, as well as the SmartRetirement design. Given our stated objective of helping the greatest num- ber of participants reach their replacement income goals at retirement, we will focus primarily on these glide paths through age 65. Cash and bonds Extended and alternative assets Equity Cash High yield Emerging equity TIPS Emerging market debt EAFE U.S. fixed income Direct real estate U.S. small cap REITs U.S. large cap Aggressive glide path Asset mix at ages: 100% 90% 25 years 45 years 65 years 80% Cash and bonds 3% 9% 35% 70% 60% Extended and 50% alternative assets 3% 6% 7% 40% 30% 20% Equity 94% 86% 59% 10% 0% 25 30 35 40 45 50 55 60 65 70 75 Age Concentrated glide path Asset mix at ages: 100% 90% 25 years 45 years 65 years 80% 70% Cash and bonds 10% 18% 50% 60% 50% 40% 30% 20% Equity 90% 82% 50% 10% 0% 25 30 35 40 45 50 55 60 65 70 75 Age Conservative glide path Asset mix at ages: 100% 90% 25 years 45 years 65 years 80% 70% 60% Cash and bonds 11% 34% 84% 50% 40% 30% 20% 10% Equity 89% 66% 17% 0% 25 30 35 40 45 50 55 60 65 70 75 Age SmartRetirement glide path Asset mix at ages: 100% 25 years 45 years 65 years 90% 80% 70% Cash and bonds 6% 13% 53% 60% 50% 40% Extended and 22% 22% 20% 30% alternative assets 20% 72% 65% 27% 10% Equity 0% 25 30 35 40 45 50 55 60 65 70 75 Age Sources: JPMorgan Asset Management, and industry prospectuses. Some asset mix numbers may not add to 100% due to rounding. 8
  • 13. Exhibit 9 — Cumulative behaviors in the Financials industry Simplified assumptions JPMorgan All Industries JPMorgan Financials industry Contributions Rates start at 6%, increase year-by-year, Contribution rates start at 6% and Contribution rates start near 6% and reaching 10% of salary by age 35 increase slowly, reaching 8% of salary increase slowly, reaching 8% of salary by age 40, and 10% not until age 55 by age 40 and 10% not until age 57 Salary raises Participants get a raise every year On average, participants get raises On average, participants get larger-than- every 2 out of 3 years average raises every other year Loans Participants don’t borrow 20% of participants borrow, on average, 20% of participants borrow, on average, 15% of account balance; 35% repeated 20% of account balance; 60% repeated Pre-retirement Premature distributions don’t happen 15% of participants over the age of 59½ 15% of participants over the age of 59½ distributions withdraw, on average, 25% of assets withdraw, on average, 25% of assets In retirement Participants withdraw a The average participant withdraws over The average participant withdraws over distributions consistent 4%—5% annually 20% at or soon after retirement 20% per year at or soon after retirement Sources: AllianceBernstein “Target-Date Retirement Funds — A Blueprint for Effective Portfolio Construction,” October 2005; JPMorgan Retirement Plan Services participant database, 2003–2006 In our simulations, broadly diversified strategies, such The impact of these behaviors on potential outcomes as SmartRetirement, resulted in the greatest number can be seen in Exhibit 10. The red line on the Financials of industry participants reaching their target income industry graph represents the increased target for replacement goal and the highest minimum and income replacement due primarily to higher-than- median portfolio balances at retirement — similar average (although less frequent) salary increases. The to results for the JPMorgan All Industries aggregate. higher-than-average salary at retirement in Financials These results emphasize the advantage of broadly — on average $72,000 in today’s dollars — results in diversified strategies in helping the greatest number a higher-than-average annuity target of $500,000 for of participants reach their income replacement goals. those participants. As we will see, a similar advantage appears to exist For participants in this industry, above-average salary for those in the Financials industry. growth also leads to slightly higher 401(k) balances at In contrast to the unique savings behavior observed in retirement, on average. However, because of only the Consumer Staples industry, the Financials industry moderate savings, combined with multiple loan activ- is very similar to the general average. Participants in ity, the increase in expected outcomes is insufficient to the Financials industry, however, have a significantly match the higher target annuity level. higher frequency of multiple loans (Exhibit 9), which The probability of falling below the target increases interacts with contributions to create a mild impact across all four target date strategies for Financials ver- on cash-flow volatility. sus the JPMorgan All Industries population. This Exhibit 10: Comparing expected portfolio balances at retirement — JPMorgan All Industries versus Financials Range of expectations with JPMorgan All Industries behavior Percentile Range of expectations with Financials industry behavior (000s) 5% (000s) 25% 1,600 1,600 50% 75% 95% 1,200 1,200 907 814 835 834 800 717 747 800 669 597 609 598 551 551 576 512 505 462 $500 424 385 410 411 402 373 $400 362 357 400 228 224 236 260 238 235 261 232 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Results are based on JPMorgan Asset Management Long-Term Capital Market Return Assumptions, 2006, JPMorgan Asset Management and industry prospectuses. See Exhibit 9 for participant behavior assumptions. All dollar values are inflation-adjusted. 9
  • 14. increased probability of shortfall, again, highlights the group of participants (64%) made less than $40,000 need for downside protection, which is best achieved and owned a smaller share of plan assets (31%). through diversification. And once the participants are separated by salary level, It is important to note that the Aggressive and Concen- the behavior characteristics observed are significantly trated strategy designs, with their higher concentration different (Exhibit 11). of return-generating but volatile equity assets, may be The simulated portfolio outcomes for these two salary able to improve expected portfolio outcomes for the groups are shown in Exhibit 12. One can see that the more fortunate participants who are expected to achieve target income replacement levels (the red lines) change “income replacement plus.” However, for those in the dramatically. bottom half of the distribution, for whom some combi- nation of loan-taking, inadequate savings, and adverse For the “high salary” participants, higher salary market conditions threatens retirement security, the growth leads to a target annual retirement income of broadly diversified SmartRetirement design can provide roughly $120,000 in today’s dollars and thus a higher- a higher degree of downside protection. As seen in than-average annuity target of $800,000. Above-aver- Exhibit 10, with its greater allocation to extended and age salary growth also leads to an increase in the range alternative investments, the SmartRetirement design is of expected portfolio outcomes for participants in this expected to get more participants over the income industry. However, a target replacement level of this Across industries, replacement hurdle — and to provide a higher floor for size is very difficult to reach with only moderate sav- those who fail to reach this goal. ings rates. Therefore the expected range of outcomes broadly diversi- falls significantly for this salary group versus its target fied target date Although the behavior of the Financials industry — for all four target date strategies. It is notable that appears to be “average,” even average behavior in an designs can help average industry can hide behavioral variations. After while both the Aggressive and SmartRetirement designs get approximately half of these participants to the most partici- examining one financial company more closely, we their goal, the SmartRetirement design provides pants achieve made some interesting observations. somewhat greater downside protection for those who retirement Once again, there was a potentially wide dispersion in fall below the target annuity level (i.e., a higher success behavior among different subsets of Financials industry expected portfolio balance). participants. We separated the participants into two For “low” salary participants, we see two contrasting salary groups: those above and those below a current movements. Lower starting salaries combined with salary level of $40,000. First, we found significant dis- moderate salary growth lead to a target annual retire- parity in asset ownership. A minority of participants ment income of only $40,000 in today’s dollars, and a (36%) earned more than $40,000, but they owned the much lower annuity target of only $225,000. At the majority of assets (69%). On the other hand, a larger Exhibit 11: Financials industry — Salary and behavior analysis JPMorgan Financials industry High salary participants Low salary participants Contributions Contribution rates start near 6% and Contribution rates start at 6% and Contribution rates start near 6% and increase slowly, reaching 8% of salary increase slowly, reaching 8% of salary increase very slowly, reaching 8% of by age 40, and 10% not until age 57 by age 40, and 10% not until age 55 salary by age 55 Salary raises On average, participants get larger-than- On average, participants get larger-than- On average, participants get larger-than- average raises every other year average raises every other year average raises every other year Loans 20% of participants borrow, on average, 20% of participants borrow, on average, 20% of participants borrow, on average, 20% of account balance; 60% repeated 20% of account balance; 55% repeated 25% of account balance; 65% repeated Pre-retirement 15% of participants over the age of 59½ 15% of participants over the age of 59½ 15% of participants over the age of 59½ distributions withdraw, on average, 25% of assets withdraw, on average, 15% of assets withdraw, on average, 30% of assets In retirement The average participant withdraws over The average participant withdraws over The average participant withdraws over distributions 20% at or soon after retirement 15% at or soon after retirement 25% at or soon after retirement Source: JPMorgan Retirement Plan Services participant database, 2003–2006 10
  • 15. Exhibit 12: Comparing Financials industry expected portfolio balances at retirement — “High” versus “Low” salary participants Range of expectations with overall Financials industry behavior Percentile (000s) 5% 1,600 25% 50% 1,200 75% 95% 907 835 834 800 669 609 576 598 505 $500 411 402 424 400 373 238 232 235 261 0 Aggressive Concentrated Conservative SmartRetirement Range of expectations given high salary behavior Range of expectations given low salary behavior (000s) (000s) 1,600 800 1,200 1,163 1,079 1,083 883 800 409 408 760 798 400 379 $800 661 309 562 272 294 536 520 261 473 230 $225 212 400 328 178 176 166 288 287 286 125 99 100 98 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Results are based on JPMorgan Asset Management Long-Term Capital Market Return Assumptions, 2006, JPMorgan Asset Management and industry prospectuses. See Exhibit 11 for participant behavior assumptions. All dollar values are inflation-adjusted. same time, their lower savings and higher withdrawals QDIA is a target date fund, may also benefit much dramatically lower their range of expected outcomes. more from a strong design focused on downside protec- What is the ultimate behavioral impact? When all tion. In this Financial company example, highly diver- these behaviors are combined, many participants end sified strategies increased the probability of lower-salary up well above the desired levels, thanks to their over- participants exceeding their retirement income targets all lower annuity target. But, again, there is no reason — from 60% (for the Aggressive design) to more than to believe that improving participants’ low savings 70% for the SmartRetirement design, while retaining through automatic features (e.g., auto-enrollment and upside capture for those with above-median outcomes. auto-escalation) will affect their withdrawal behavior (Note: While the savings shortfall for “high salary” employ- — i.e., plan sponsors cannot be confident funds cap- ees is indisputable, their inadequate contribution rate may tured by forcing higher savings will actually stay reflect something other than poor savings practices. Fixed-dol- invested in the plan. lar contribution caps may be restraining their contribution We hypothesize that, relative to those with higher sala- rates as a percent of salary, thereby hampering their ability ries, lower-salary participants may not only be more to reach adequate savings levels through their 401(k) plans, likely to default into a plan’s QDIA3 but, when the especially given their higher annuity targets.) 3 Qualified Default Investment Alternative (QDIA) 11
  • 16. Conclusion From industry to industry, there will always be variabil- As a result, these types of strategies, regardless of the ity around participants’ cash flow behavior — Exhibit 13 sponsor’s industry, may be the most appropriate selec- shows the variability of ten industries compared to the tion for a qualified default investment vehicle. Appen- JPMorgan All Industries average. There may even be dix A summarizes the range of expected portfolio out- variability within specific plans, particularly among dif- comes for all ten of the industries we studied, taking ferent salary levels. Understanding these variations, and into account specific contribution and withdrawal pat- their impact on participants’ success rates, is essential to terns for those industries. The broadly diversified both fund selection and plan design. approach appears to deliver superior results, better than those of less-diversified, more traditional strategies. One thing does not change from plan to plan. Our research indicates that every plan is likely to vary to As discussed in our previous paper, target date strate- some extent from “simplified assumptions” about par- gies represent a quantum leap in defined contribution ticipant behavior. Consequently, every plan will face investments. They are designed to provide one pack- the issue of volatility in both contribution and with- age in which the individual’s assets are allocated to the drawal rates, emphasizing the importance of downside right markets, fully invested all the time and profes- protection for all participants. Highly diversified tar- sionally managed. But our latest research shows that get date strategies that include extended and alterna- not all target date fund designs are equal: Greater tive assets throughout the investment horizon and are portfolio diversity, providing greater downside protec- designed to provide this downside protection may tion, may improve outcomes for participants in all help the greatest number of participants reach their industries, especially taking into account cash-flow target account balances at retirement. volatility and other behavioral challenges. Exhibit 13 — Industry versus JPMorgan All Industries average* Pre-retirement Industry values compared to Salary raises Contributions Loans distributions JPMorgan All Industries average Rates start at 6%, = Well above average Participants get increase year-by- Premature Standard a real raise year, reaching 10% Participants distributions = Above average assumptions every year of salary by age 35 don’t borrow don’t happen Contributions start A = Close to average Real-world On average, at 6%, increase slowly 15% of participants 20% of participants = Below average JPMorgan participants get to 8% by age 40 and borrow, on average, over the age of 591/2 All Industries raises every 2 don’t reach 10% 15% of account withdraw, on average, = Well below average average out of 3 years until age 55 balance 25% of assets Consumer Durables A = Potentially beneficial Consumer Services A = Potentially detrimental Consumer Staples A A Energy A A A Financials A A Healthcare A Industrials A Information Technology Materials Utilities A Sources: JPMorgan Asset Management, AllianceBernstein “Target-Date Retirement Funds — A Blueprint for Effective Portfolio Construction,” October 2005; JPMorgan Retirement Plan Services participant database, 2003–2006. * For further details, see our supplemental industry summary sheets — available at jpmorgan.com/insight or through your JPMorgan representative, if not provided with this report. 12
  • 17. These target date strategies can be so effective, in part, stronger savings, they also had larger average with- because they have been designed specifically to address drawals prior to retirement, which can potentially behaviors seen in real-world observation. Moreover, diminish any advantage acquired from higher savings short of radically changing plan design features gov- rates. In our original whitepaper (Ready! Fire! Aim? erning savings, loans and withdrawals, choosing the page 22), the impact of large withdrawals, even in right target date strategy is one step that plan spon- the presence of strong savings, was shown to have a sors can take to reliably improve participant outcomes dramatic impact on retirement account balances. — helping the greatest number of participants achieve We would go even further to suggest that participants their retirement funding objectives. who lack a commitment to saving and investing — i.e., With regard to behavior modification, we fear that those who must be auto-enrolled and auto-escalated — many approaches currently being contemplated or used may exhibit a wider range of problematic savings (e.g., auto-enrollment, auto-escalation) may not be suf- behaviors. In addition, these less-engaged participants ficient to maximize overall success rates. Plan sponsors are likely to remain in the default vehicle, and they will may have to rethink some features that have become represent a high percentage of target date investors in commonplace, such as loans and early withdrawals. plans where the default vehicle is a target date fund. These features were adopted for sound reasons, but they So if participant behavior is resistant to change, and may be having unintended and potentially serious con- those most at risk for missing their retirement fund- Choosing a target sequences for participants’ portfolio outcomes. And we ing targets are also likely to rely on the default vehi- date design may question whether the latest changes to such features — cle, plan sponsors would then do well to choose a e.g., those in the current version of the Pension be among plan target date strategy that can address both issues. Protection Act — will produce the necessary behavioral sponsors’ most According to our research, target date strategies that results. Based on observations to date, we hypothesize are well-diversified throughout the investment hori- critical decisions that: zon are most effective in overcoming negative behav- • Auto-enrollment may improve participation rates, ioral influences and delivering downside protection but it is not clear to us that participants who choose to those who need it most. not to act, and have to be enrolled by default, will actively manage their contribution rates and invest- In future research, we hope to provide a clearer picture ment choices. They will likely save only to the of the behavioral profile of the typical target date amount defaulted. investor, which may help plan sponsors further refine their fund selection and plan features. In the mean- • Likewise, auto-escalation may force inactive partici- time, we can say with confidence that, regardless of pants to increase their contribution rates and help industry, highly diversified target date strategies help them save more, but most auto-escalation features the greatest number of participants achieve income start with contribution rates of only 3% and replacement security, and hopefully a comfortable increase up to only 6%, which our research indicates retirement — and this, after all, is the highest fidu- is an inadequate savings level for retirement.4 ciary role and objective of plan sponsors. • In addition, auto-enrollment and auto-escalation may negatively impact participants’ withdrawal and For further details, see our supplemental industry summary loan behavior. We observed that, even while certain sheets and our previous research report Ready! Fire! Aim? plans and industries (e.g., Info Tech) tended to have — available at jpmorgan.com/insight or through your JPMorgan representative. 4 These numbers do not include an employer contribution, which we assume for modeling purposes in our research, to be 3%. 13
  • 18. Appendices Appendix A — Potential portfolio outcomes comparable, the SmartRetirement portfolio delivers a based on industry-specific behavior patterns* tighter range of outcomes, suggesting a more efficient There are two key observations about these industry- use of risk. Second, the highly diversified portfolio specific charts. First, while the expected (i.e., mean or helps the greatest number of participants reach their 50th percentile) return profiles of the Aggressive and annuity targets for all industries included in this study. highly diversified SmartRetirement portfolios are Range of expected balances with JPMorgan All Industries behavior assumptions (000s) Percentile 5% 1,500 25% 1,200 50% 75% 900 814 95% 747 717 597 600 551 512 551 462 410 385 362 $400 357 300 228 236 260 224 0 Aggressive Concentrated Conservative SmartRetirement Range of expected balances with Consumer Durables Range of expected balances with Consumer Services industry behavior industry behavior (000s) (000s) 800 1,400 1,200 600 1,000 800 753 389 679 676 400 365 365 600 550 299 512 479 501 269 254 267 $250 225 419 195 $400 353 343 371 185 180 169 318 200 122 206 204 206 230 110 109 110 200 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Range of expected balances with Consumer Staples industry behavior Range of expected balances with Energy industry behavior (000s) (000s) 1,200 1,400 1,000 1,200 1,000 800 681 626 636 800 740 702 693 600 466 500 471 600 554 444 502 485 505 385 $400 329 318 350 422 365 299 400 346 342 $350 316 199 201 205 225 225 200 202 204 202 200 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement * For further details, see our supplemental industry summary sheets — available at jpmorgan.com/insight or through your JPMorgan representative, if not provided with this report. 14
  • 19. Interpreting exhibited results: These charts show the range of outcomes (i.e., expected account balances at retirement) from scenario testing of four target date fund designs, based on JPMorgan’s industry behavior and capital market assumptions. The colored box for each fund design marks the 25th, 50th and 75th percentile outcomes, from top (best) to bottom (worst). The vertical black lines reaching out from the top and bottom of the box show the range of outcomes up to the 5th and down to the 95th percentile. For each industry, the horizontal red line marks the target account balance needed to achieve income replacement. (See Appendices B and C for JPMorgan Asset Management Capital Market Assumptions — 2006 and the calculation of income replacement targets.) Range of expected balances with Financials Range of expected balances with Healthcare industry behavior industry behavior (000s) (000s) 1,600 1,200 1,200 900 907 655 835 834 606 598 800 600 669 480 609 598 448 432 444 576 $450 505 371 $500 411 424 312 303 325 402 373 284 400 300 238 232 235 261 182 184 182 204 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Range of expected balances with Industrials Range of expected balances with Information Technology industry behavior industry behavior (000s) (000s) 1,500 1,600 1,200 1,200 900 886 753 786 796 680 683 800 639 553 605 559 581 600 516 487 505 $500 495 $450 424 408 391 374 423 357 347 373 400 322 300 234 232 235 240 267 212 210 209 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement Range of expected balances with Materials Range of expected balances with Utilities industry behavior industry behavior (000s) (000s) 1,200 1,500 900 1,200 626 900 600 572 574 762 712 707 461 423 402 424 600 568 530 $400 355 521 507 289 285 309 448 300 267 $450 364 365 385 341 171 172 174 193 300 244 215 219 219 0 0 Aggressive Concentrated Conservative SmartRetirement Aggressive Concentrated Conservative SmartRetirement For all charts in Appendix A, results are based on JPMorgan Asset Management Long-Term Capital Market Return Assumptions, 2006, JPMorgan Asset Management and industry prospectuses. All dollar values are inflation-adjusted. 15
  • 20. Appendix B: JPMorgan Asset Management long-term capital market return assumptions* Expected 10–15 year annualized compound USD returns Rationale U.S. Inflation 2.50% Inflation to remain generally well-contained, but risks are to the upside given tight supply-demand balance in energy. U.S. Real GDP 3.25% Productivity growth expected to remain strong, but below the exceptional gains of recent years. U.S. Cash 4.25% Higher real short-term rates than in recent years, as Fed needs to work hard to contain inflation. U.S. Treasuries (10-yr) TR 4.75% 10-yr yields to rise toward equilibrium level of 5.25%, but decline in bond prices to hurt returns as yields rise. U.S. Aggregate TR 5.25% Spreads near equilibrium, but rise in Treasury yields to hurt returns until adjustment is complete. U.S. Long Duration Govt/Corp 5.25% Bond yields expected to rise, but search for yield expected to put cap on longer term rates. U.S. TIPS TR (nominal) 4.75% Real yields expected to rise, hurting returns in early years. U.S. High Yield TR 7.25% Spreads assumed to widen from current historically low levels. Some haircut to returns from expected defaults. Non-U.S. World Govt. Bond Index TR (local currency) 3.00% Bond yields expected to rise, hurting returns in early years. Non-U.S. World Govt. Bond 4.75% Decline in the dollar (particularly against Japan, whose weight in WGBI is large) to provide an average Index TR (USD) 175bp per annum boost to returns. Emerging Market Debt TR 7.50% Spreads assumed to widen, but by less than High Yield; assumes secularly improving credit quality of EM universe. U.S. Municipal TR 4.00% Bond yields expected to rise, hurting returns in early years. U.S. Large Cap TR 7.25% Sum of below building blocks (EPS Growth + Dividend Yield + Impact of Changes in P/E Multiples). U.S. Large Cap EPS Growth 5.50% Boost from productivity acceleration is waning. EPS growth expected to be slightly below nominal GDP growth. U.S. Large Cap Dividend Yield 2.25% Dividend payout ratios expected to rise. U.S. Large Cap P/E Impact on Return -0.50% Expect minor amount of multiple contraction, taking multiples back toward averages of past low inflation periods. U.S. Mid Cap TR 7.50% 25 bps premium over Large-Cap. Small-Caps have become comparatively expensive and no longer appear to U.S. Small Cap TR 7.50% warrant a return premium relative to Mid-Caps. U.S. Large Cap Growth TR 7.00% Value expected to outperform growth over long time periods. U.S. Large Cap Value TR 7.50% EAFE TR (local currency) 7.75% Non-U.S. economic and (especially) profit performance expected to improve, fueling a small rise in P/E multiples. EAFE TR (USD) 8.75% Decline in the dollar (particularly against Japan) to provide an average 100bp per annum boost to USD EAFE returns. Emerging Market Equity TR (USD) 8.75% Improved economic and profit performance by EM economies. Currencies likely to rise over time vs. USD. Private Equity TR (Industry median) 8.50% Forecast is modestly above those on higher-risk categories of public equity. Only top quartile managers can be expected to substantially beat public market returns. (See note below.) U.S. Direct Real Estate (unlevered) 6.75% Less than equity return, more than fixed income. Reflects strong operating income yields. REITs 7.00% A bit higher than return on direct real estate due to leverage. Premium constrained due to comparatively expensive REIT valuations. Hedge Fund (non-directional) TR 5.75% Hedge Funds to deliver only moderate returns but with comparatively low risk. Top managers expected to Hedge Fund (directional) TR 7.00% beat these returns. (See note below.) As of November 30, 2005* Note: Private Equity and Hedge Funds are unlike other asset classes shown above, in that there is no underlying investible index. The return estimates shown above for these assets are our estimates of industry medians; the dispersion of returns among different managers in these asset classes is typically far wider than in traditional assets. Given the complex risk-reward tradeoff in these assets, we counsel clients to rely on judgment rather than quantitative optimization approaches in setting strategic allocations to these asset classes. Please note all information shown is based on assumptions; therefore, exclusive reliance on these assumptions is incomplete and not advised. The assumptions should not be relied upon as a recommendation to invest in any particular asset class. The individual asset class assumptions are not a promise of future performance. Note that these asset class assumptions are passive-only; they do not consider the impact of active management. Return estimates are on a compound or internal rate of return (IRR) basis. Equivalent arithmetic averages, as well as additional notes, are shown on the next page. * JPMorgan Asset Management’s long-term capital market return assumptions as of November 30, 2005 were used in this and our earlier research report on target date funds. For our latest assumptions, as of November 30, 2007, please visit our website at jpmorgan.com/insight or contact your JPMorgan representative. 16
  • 21. Appendix B: JPMorgan Asset Management long-term capital market return assumptions (continued)* Annualized Compound USD Return Correlation Matrix Non-U.S. World Govt. (unhedged) Non-U.S. World Govt. (hedged) U.S. Long Duration Govt/Corp Hedge Fund (non-directional) Mean Expected USD Return Hedge Fund (directional) Emerging Market Equity U.S. Large Cap Growth Emerging Market Debt U.S. Direct Real Estate U.S. Large Cap Value U.S. Treasury Index Expected Volatility EAFE (unhedged) U.S. Aggregate U.S. High Yield U.S. Small Cap U.S. Large Cap U.S. Municipal EAFE (hedged) Private Equity U.S. Inflation U.S. Mid Cap Hedge Fund U.S. Cash U.S. TIPS REITs Fixed U.S. Inflation 1.0% 2.50% 2.50% 1.00 Income U.S. Cash 0.5% 4.25% 4.25% 0.00 1.00 U.S. Treasury Index 4.7% 4.50% 4.60% -0.08 0.11 1.00 U.S. TIPS 4.9% 4.75% 4.87% 0.07 -0.06 0.77 1.00 U.S. Aggregate 3.7% 5.25% 5.32% -0.09 0.12 0.97 0.75 1.00 U.S. Municipal 3.3% 4.00% 4.05% -0.09 0.08 0.87 0.72 0.88 1.00 U.S. Long Duration Govt./Corp. 8.0% 5.25% 5.55% -0.14 0.02 0.95 0.77 0.96 0.86 1.00 U.S. High Yield 10.0% 7.25% 7.71% -0.13 -0.11 0.00 0.04 0.14 0.14 0.22 1.00 Non-U.S. World Govt. (hedged) 2.6% 4.75% 4.78% -0.03 0.30 0.73 0.52 0.72 0.65 0.70 0.05 1.00 Non-U.S. World Govt. (unhedged) 8.1% 4.75% 5.06% -0.07 -0.18 0.43 0.41 0.42 0.39 0.38 0.00 0.32 1.00 Emerging Market Debt 14.4% 7.50% 8.44% 0.03 0.00 0.08 0.17 0.18 0.16 0.19 0.49 0.13 0.04 1.00 Equities U.S. Large Cap 15.6% 7.25% 8.36% -0.10 0.05 -0.19 -0.16 -0.07 -0.11 -0.04 0.49 -0.06 -0.04 0.55 1.00 U.S. Large Cap Value 14.5% 7.50% 8.46% -0.10 0.04 -0.18 -0.11 -0.07 -0.11 -0.04 0.45 -0.02 0.00 0.55 0.90 1.00 U.S. Large Cap Growth 19.6% 7.00% 8.73% -0.08 0.04 -0.18 -0.18 -0.08 -0.12 -0.05 0.47 -0.11 -0.06 0.49 0.94 0.71 1.00 U.S. Mid Cap 17.6% 7.50% 8.89% -0.11 0.02 -0.20 -0.13 -0.11 -0.12 -0.07 0.49 -0.15 0.01 0.57 0.86 0.82 0.82 1.00 U.S. Small Cap 20.2% 7.50% 9.32% -0.11 -0.04 -0.24 -0.16 -0.14 -0.15 -0.09 0.53 -0.16 0.00 0.53 0.71 0.61 0.74 0.88 1.00 EAFE (unhedged) 14.9% 8.75% 9.74% -0.08 -0.11 -0.22 -0.13 -0.13 -0.12 -0.09 0.46 -0.15 0.20 0.53 0.79 0.71 0.74 0.75 0.71 1.00 EAFE (hedged) 14.8% 8.75% 9.74% -0.04 0.05 -0.33 -0.26 -0.23 -0.23 -0.17 0.48 -0.17 -0.26 0.54 0.81 0.72 0.77 0.73 0.69 0.85 1.00 Emerging Market Equity 23.6% 8.75%11.18% -0.03 -0.19 -0.29 -0.12 -0.19 -0.16 -0.15 0.52 -0.20 -0.04 0.68 0.70 0.64 0.67 0.73 0.72 0.75 0.74 1.00 REITs 13.6% 7.00% 7.85% -0.03 -0.08 -0.02 0.11 0.04 0.09 0.07 0.31 0.08 0.16 0.38 0.29 0.42 0.18 0.40 0.45 0.29 0.22 0.37 1.00 U.S. Direct Real Estate 7.1% 6.75% 6.99% -0.05 0.15 0.25 0.22 0.29 0.26 0.28 0.19 0.26 0.14 0.26 0.25 0.28 0.20 0.26 0.23 0.18 0.15 0.16 0.40 1.00 Other Hedge Fund 6.0% 6.50% 6.67% 0.01 0.06 -0.08 -0.03 -0.01 0.02 0.03 0.45 -0.01 -0.13 0.59 0.54 0.43 0.57 0.61 0.69 0.57 0.63 0.65 0.26 0.18 1.00 Hedge Fund (non-directional) 4.0% 5.75% 5.83% -0.03 0.35 -0.04 0.03 0.04 0.04 0.05 0.48 0.04 -0.08 0.55 0.45 0.44 0.41 0.52 0.54 0.37 0.43 0.41 0.29 0.23 0.67 1.00 Hedge Fund (directional) 7.0% 7.00% 7.23% -0.02 0.01 -0.13 -0.04 -0.04 -0.01 0.00 0.53 -0.05 -0.04 0.64 0.67 0.56 0.68 0.75 0.82 0.69 0.71 0.73 0.35 0.22 0.85 0.65 1.00 Private Equity 30.0% 8.50%12.30% -0.05 -0.08 -0.21 -0.12 -0.12 -0.10 -0.06 0.53 -0.18 -0.02 0.46 0.56 0.40 0.64 0.70 0.91 0.60 0.59 0.67 0.33 0.16 0.60 0.52 0.82 1.00 As of November 30, 2005* (continued from prior page) Expected returns employ proprietary projections of the “equilibrium” returns of each asset class (as well as equilibrium estimates of their future volatility). We estimate the “equilibrium” performance of an asset class or strategy by analyzing current economic and market conditions and historical market trends. Equilibrium estimates represent our projection of the central tendency (going out over a very long time period) around which market returns may fluctuate, because they reflect what we believe is the value inherent in each market. It is possible that actual returns will vary considerably from this equilibrium, even for a number of years. References to future returns for either asset allocation strategies or asset classes are not promises or even estimates of actual returns a client portfolio may achieve. Opinions and estimates offered constitute our judgment and are subject to change without notice, as are statements of financial market trends, which are based on current market conditions. We believe the information provided here is reliable, but do not warrant its accuracy or completeness. This material is not intended as an offer or solicitation for the purchase or sale of any financial instrument. The views and strategies described may not be suitable for all investors. This material has been prepared for information purposes only, and is not intended to provide, and should not be relied on for, accounting, legal or tax advice. * JPMorgan Asset Management’s long-term capital market return assumptions as of November 30, 2005 were used in this and our earlier research report on target date funds. For our latest assumptions, as of November 30, 2007, please visit our website at jpmorgan.com/insight or contact your JPMorgan representative. 17
  • 22. Appendix C — Income Replacement Summary increases to 77%, but Social Security benefits currently Although salary levels over the course of a partici- replace only 35% of income. This leaves 42% of work- pant’s career determine the dollar amounts he or she ing income to be replaced by alternate savings, such as is contributing every year into a 401(k), the salary an individual’s 401(k) plan. level obtained by the date of retirement determines Income replacement can also be expressed as a target the lifestyle to which he or she has become accus- portfolio level — the minimum amount needed, tomed and the amount of wealth on which he or she hypothetically, to purchase an annuity that would will need to live. provide the required level of income replacement for Research on retirement has concluded that the living life. Estimates of the lump sums can differ, depend- expenses required to maintain a working year’s life- ing on the return embedded in the annuity and style in retirement decrease significantly. There are whether the income stream adjusts with inflation. many factors that lead to the decline in required Although there are a number of methods for measur- gross income, such as a decline in income taxes, the ing the value of a portfolio at retirement, we use the start of social security benefits, the elimination of price of an annuity to derive an equal measure for many working expenses and the culmination of the 401(k) balance needed to provide a minimum many savings goals (such as retirement). On average, income replacement level. an individual will need to replace around 80% (or In our analyses, we observed sub-populations of retirees need an 80% replacement ratio) of their working earning a wide range of final salaries. The average income in retirement to maintain his or her former across the population was approximately $65,000, but standard of living.1 ranged from $50,000 to over $80,000 across industry However, many of the factors that help determine the groups. Market prices of annuities replacing 35% of amount of income replacement needed depend on an the average $65,000 income were about $400,000 in individual’s circumstances. One major factor that will late 2006. Alternatively, final salaries of $80,000 alter the required level of income replacement is the would require around $550,000 to replace around individual’s salary that is to be partially replaced. At 42% of that income.2 Of course, there are many addi- lower levels of income, a small replacement ratio is tional factors that can alter an individual’s required required, due to lower income tax rates in retirement income replacement, such as medical expenses, addi- and proportionally greater Social Security benefits. For tional savings, or continued employment. We take the working incomes of around $65,000, the total replace- view that structuring target date strategies to accom- ment ratio is only 75% and Social Security replaces modate such highly unpredictable and diverse post- around 40%, so the remaining replacement rate retirement cash flows could lead to poor target date declines to about 35%. However, for higher working fund design. We believe a more prudent approach is to incomes of around $80,000, the total replacement ratio help as many participants as possible meet the basic income replacement goal defined in this paper. 1 The Aon Consulting/Georgia State University 2004 Retirement Income Replacement Ratio Study, Aon Consulting. 2 Our analysis assumes a 5% return and a 2.5% inflation rate. Academic research and industry pricing center around these numbers but can vary dramatically. Annuity amounts are inflation-adjusted to represent today’s dollars. 18
  • 23. Opinions, estimates, assumptions and simulations offered constitute our judgment and are subject to change without notice, as are statements of financial market trends, which are based on current market conditions. We believe the information provided here is reliable, but do not warrant its accuracy or completeness. This material is not intended as an offer or solicitation for the purchase or sale of any financial instrument. References to specific securities, asset classes, and financial markets are for illustrative purposes only and are not intended to be, and should not be interpreted as, recommendations. These materials have been provided to you for information purposes only and may not be relied upon by you in evaluating the merits of investing in any securities referred to herein. Past performance is not indicative of future results. Indices do not include fees or operating expenses and are not available for actual investment. Indices presented, if any, are representative of various broad base asset classes. They are unmanaged and shown for illustrative purposes only. The views and strategies described may not be suitable for all investors. This material has been prepared for informational purposes only, and is not intended to provide, and should not be relied on for, accounting, legal or tax advice. You should consult your tax or legal advisor regarding such matters. JPMorgan Asset Management is the marketing name for the asset management businesses of JPMorgan Chase & Co. and its affiliates worldwide which includes but is not limited to J.P. Morgan Investment Management Inc., JPMorgan Investment Advisors, Inc., Security Capital Research & Management Incorporated and J.P. Morgan Alternative Asset Management, Inc. www.jpmorgan.com/insight © JPMorgan Chase & Co., February 2008 IMWP_SMARTR_INDUSTRY
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